Quantile/expectile regression, and extreme data analysis
Quantile/expectile regression, and extreme data analysis
Quantile/expectile regression, and extreme data analysis
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Expectile <strong>regression</strong><br />
Expected shortfall† I<br />
Value at Risk<br />
The expected shortfall (ES) 2 is a concept used in financial mathematics<br />
to measure portfolio risk. Aka<br />
Conditional Value at Risk (CVaR),<br />
expected tail loss (ETL) <strong>and</strong><br />
worst conditional expectation (WCE).<br />
The ES at the 100τ% level is the expected return on the portfolio in the<br />
worst 100τ% of the cases. It is often defined as<br />
ES(τ) = E(Y |Y < a) (11)<br />
where a is determined by P(X < a) = τ <strong>and</strong> τ is the given threshold.<br />
© T. W. Yee (University of Auckl<strong>and</strong>) <strong>Quantile</strong>/<strong>expectile</strong> <strong>regression</strong>, <strong>and</strong> <strong>extreme</strong> <strong>data</strong> <strong>analysis</strong> 18 July 2012 @ Cagliari 40/101/
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